One of the problems related with using this approach is computational complexity while working with 3D objects. Direct applying off-the-shelf RL methods does not produce satisfying results. Therefore, following the works [1]}, [2]} we also consider to use Imitation Learning for quick-start pre-training of the network. The difference of our approach is we use a heuristic method to generate demonstration data and effectively search for optimal policies. This boosts the performance of our method and results in visually acceptable 3D reconstructions.
